public Network(HyperParameters hyperParameters, params int[] nodeCounts)
{
mParameters = hyperParameters;
switch (mParameters.CostFunctionName)
{
case "QuadraticCost":
mCostFunction = new QuadraticCost();
break;
case "CrossEntropyCost":
mCostFunction = new CrossEntropyCost();
break;
default:
throw new ArgumentException(string.Format("Invalid cost function name:'{0}'", mParameters.CostFunctionName));
}
if (nodeCounts == null || nodeCounts.Length == 0)
{
return;
}
mLayers = new Layer[nodeCounts.Length];
for (int i = 0; i < mLayers.Length; i++)
{
mLayers[i] = new Layer(nodeCounts[i], i == 0 ? 0 : nodeCounts[i - 1]);
}
}
public void Train(HyperParameters parameters, List <(Vector <double> Image, Vector <double> Label)> data, Func <Vector <double>, Vector <double>, bool> areEqual, List <(Vector <double> Image, Vector <double> Label)> testData = null)
